---
title: "COVID-19 Dashboard"
author: Mena WANG
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
    theme: cerulean
    social: [ "twitter", "linkedin", "menu" ]
---

```{r setup, include=FALSE}
# dashboard
library(flexdashboard)
library(knitr)
library(grid) 
library(lubridate)


# theme
library(ggthemes)
#devtools::install_github("b-rodrigues/brotools")
#library(brotools)

# data wrangling
library(tidyverse)
library(lubridate)

# data visualization
library(plotly)
library(gganimate)

# map
library(rmapshaper)
#remotes::install_github("srkobakian/sugarbag")
#library(sugarbag)
```

World 
=======================================================================

```{r time_series}
# time series of confirmed cases in each area
df <- read_csv(
  file = 'https://covid.ourworldindata.org/data/owid-covid-data.csv') 
Now=Sys.Date()

#rename key variables
dfALL<-df %>% 
  rename(Entity=location,
         Date=date,
         Continent=continent) %>% 
  mutate(Date=as.Date(Date),
         Entity=as.factor(Entity),
         Entity=recode(Entity,
                       "United States"="USA",
                       "United Kindom"="U.K."))

# #Remove unwanted cases
Continents <- c("Asia","World","North America","Europe","Oceania","South America","Africa","European Union","International")
UKParts <- c("Scotland","England", "Northern Ireland","Wales")

dfALL <- dfALL %>% 
  filter(!Entity %in% Continents,
         !Entity %in% UKParts)

###Choose Vs and Dates
dfALL<-dfALL %>% 
  select(Entity,
         Date,
         Continent,
         DailyNew=new_cases_smoothed,
         DailyNewPM=new_cases_smoothed_per_million,
         total_vaccinations_per_hundred,
         reproduction_rate)

Daily <- dfALL %>% 
  filter(Date >= "2021-01-01")

###############Choose entities with top new cases
Today=Daily %>% 
  filter(Date==(max(Date)-1))

Top10List<-Daily %>% 
  #sometimes the latest date only has very few observations
  filter(Date==(max(Date)-1)) %>% 
  arrange(desc(DailyNew)) %>% 
  slice_max(DailyNew,n=10) %>% 
  #a variable representing latest DailyNew, then rank entities by it in the plot
  select(Entity,
         DailyNewToday=DailyNew)

Top5List <-Top10List %>% 
  slice_max(DailyNewToday,n=5)

Top10 <- left_join(Top10List,Daily) 
Top5 <- left_join(Top5List,Daily)

```

Column {.tabset out.width="100%"}
-----------------------------------------------------------------------

### `r paste0("Entities with the most daily new cases at ", Sys.Date())` 

```{r total_confirmed}
ggplot(Top10, aes(x=Date,y=DailyNew,color=Continent)) + 
  geom_line(size=1)+
  #subplots by entity, ordered by DailyNewToday
  facet_wrap(facets=~reorder(Entity,-DailyNewToday), 
             nrow=2,
             scales="free_y")+
  #expand_limits(y=0)+
  #no decimal place, 1000 represented by K
  scale_y_continuous(labels=scales::number_format(scale=.001,suffix="K",accuracy=1))+
  labs(title="Countries with the Highest Daily New Cases",
       subtitle=glue::glue("Last Updated {Now}",),
       y="",
       x="",
       caption="By: @mena_wang  Data: OurWorldInData")+
  theme_minimal()+
  theme(plot.title=element_text(face="bold"),
        plot.subtitle=element_text(hjust=1,color="gray50"),
        plot.caption=element_text(hjust=1,color="gray50"),        
        legend.position = "bottom",
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 90))
```


### `r paste0("Entities with the most daily new cases and vaccines at ", Sys.Date())` 

```{r}
p1.1=ggplot(Top5,aes(x=Date,y=total_vaccinations_per_hundred))+
  geom_line(size=1,color="turquoise3")+
  facet_wrap(facets=~reorder(Entity,-DailyNewToday),
             nrow=1)+
  labs(y="Vaccine Doses (per hundred)",
       x="",
       subtitle=glue::glue("Last Updated {Now}"))+
  theme_minimal()+
  theme(plot.subtitle=element_text(hjust=1,color="grey40",face="italic"),
        axis.text.x=element_blank())

p2.1=ggplot(Top5, aes(x=Date,y=DailyNewPM)) + 
  geom_line(size=1,color="tomato3")+
  #the countries ordered by DailyNewCases
  scale_y_continuous(labels=scales::comma_format(accuracy=1))+
  #if I force to begin with 0, free_y doesn't work
  #limits=c(0,max(Daily$DailyNewToday)))+
  facet_wrap(facets=~reorder(Entity,-DailyNewToday),
             #scales="free_y",
             nrow = 1)+
  labs(y="Daily New Cases (per million)",
       x="",
       caption="By: @mena_wang   Data: ourworldindata")+
  theme_minimal()+
  theme(axis.text.x = element_text(angle = 90))

#p2.2 DailyNew (not per million, see above)

library(grid)
p_combined1<-gridExtra::grid.arrange(p1.1,p2.1,
                                     nrow=2,
                                     top = textGrob("Five Countries with the Highest Daily New Cases",
                                                    gp = gpar(fontsize = 12, font = 2)))

```

Victoria 
=======================================================================